Scaling-up ecological understanding with remote sensing and causal inference.

Decades of empirical ecological research have focused on understanding ecological dynamics at local scales. Remote sensing products can help to scale-up ecological understanding to support management actions that need to be implemented across large spatial extents. This new avenue for remote sensing applications requires careful consideration of sources of potential bias that can lead to spurious causal relationships.

Temporal variability and predictability predict alpine plant community composition and distribution patterns.

One of the most reliable features of natural systems is that they change through time. Theory predicts that temporally fluctuating conditions shape community composition, species distribution patterns, and life history variation, yet features of temporal variability are rarely incorporated into studies of species-environment associations. In this study, we evaluated how two components of temporal environmental variation-variability and predictability-impact plant community composition and species distribution patterns in the alpine tundra of the Southern Rocky Mountains in Colorado (USA).

Biodiversity in changing environments: An external-driver internal-topology framework to guide intervention.

Accompanying the climate crisis is the more enigmatic biodiversity crisis. Rapid reorganization of biodiversity due to global environmental change has defied prediction and tested the basic tenets of conservation and restoration. Conceptual and practical innovation is needed to support decision making in the face of these unprecedented shifts.

Drivers of bacterial and fungal root endophyte communities: understanding the relative influence of host plant, environment, and space.

Bacterial and fungal root endophytes can impact the fitness of their host plants, but the relative importance of drivers for root endophyte communities is not well known. Host plant species, the composition and density of the surrounding plants, space, and abiotic drivers could significantly affect bacterial and fungal root endophyte communities. We investigated their influence in endophyte communities of alpine plants across a harsh high mountain landscape using high-throughput sequencing.

Climate disequilibrium dominates uncertainty in long-term projections of primary productivity.

Rapid climate change may exceed ecosystems' capacities to respond through processes including phenotypic plasticity, compositional turnover and evolutionary adaption. However, consequences of the resulting climate disequilibria for ecosystem functioning are rarely considered in projections of climate change impacts. Combining statistical models fit to historical climate data and remotely-sensed estimates of herbaceous net primary productivity with an ensemble of climate models, we demonstrate that assumptions concerning the magnitude of climate disequilibrium are a dominant source of uncertainty: models assuming maximum disequilibrium project widespread decreases in productivity in the western US by 2100, while models assuming minimal disequilibrium project productivity increases.